Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence 2018
DOI: 10.24963/ijcai.2018/548
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Impression Allocation for Combating Fraud in E-commerce Via Deep Reinforcement Learning with Action Norm Penalty

Abstract: Conducting fraud transactions has become popular among e-commerce sellers to make their products favorable to the platform and buyers, which decreases the utilization efficiency of buyer impressions and jeopardizes the business environment. Fraud detection techniques are necessary but not enough for the platform since it is impossible to recognize all the fraud transactions. In this paper, we focus on improving the platform's impression allocation mechanism to maximize its profit and reduce the sellers' fraudu… Show more

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Cited by 31 publications
(13 citation statements)
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“…Mengingat maraknya penipuan pada situs e-commerce yang dapat mengakibatkan kerugian finansial yang cukup besar, sebagai konsumen perlu adanya pengetahuan mengenai jenis penipuan yang umum terjadi dan metode pencegahan yang digunakan untuk mendeteksi penipuan agar terhindar dari berbagai kerugian. Beberapa penelitian sebelumnya hanya membahas tentang identifikasi dan metode pencegahan penipuan e-commerce ( Makarti, 2011;Chang & Chang, 2012;Syed & Shabbir, 2013;Valentin, 2013;Caldeira, Brandao, & Pereira, 2014;Leung, Lai, Chen, & Wan, 2014;Massa & Valverde, 2014;Hwang & Lai, 2015;JRana & Baria, 2015;Singh & Singh, 2015;Abdallah, Maarof, & Zainal, 2016;Beránek, Nýdl, & Remeš, 2016;Gerlach, Pavlovic, & Gerlach, 2016;Lima & Pereira, 2016;Yang et al, 2016;Ramadhan & Amelia, 2016;Sun et al, 2017;Prisha, Neo, Ong, & Teo, 2017;Raghava-Raju, 2017;Shaji & Panchal, 2017;Wiralestari, 2017;Renjith, 2018;Weng et al, 2018;Zhao et al, 2018;Zheng et al, 2018); Amasiatu Amiruddin et al, 2019;Carta et al, 2019;Raghavan & Gayar, 2019;Shah et al, 2019;Soomro et al, 2019. Sementara penelitian lainnya lebih fokus pada penipuan sistem pembayaran dan penipuan terkait dengan pelanggan (Keraf & Hidup, 2010;Rofiq & Mula, 2010;Raj & Portia, 2011;Hu, Liu, & Sambamurthy, 2011;…”
Section: Pendahuluanunclassified
See 1 more Smart Citation
“…Mengingat maraknya penipuan pada situs e-commerce yang dapat mengakibatkan kerugian finansial yang cukup besar, sebagai konsumen perlu adanya pengetahuan mengenai jenis penipuan yang umum terjadi dan metode pencegahan yang digunakan untuk mendeteksi penipuan agar terhindar dari berbagai kerugian. Beberapa penelitian sebelumnya hanya membahas tentang identifikasi dan metode pencegahan penipuan e-commerce ( Makarti, 2011;Chang & Chang, 2012;Syed & Shabbir, 2013;Valentin, 2013;Caldeira, Brandao, & Pereira, 2014;Leung, Lai, Chen, & Wan, 2014;Massa & Valverde, 2014;Hwang & Lai, 2015;JRana & Baria, 2015;Singh & Singh, 2015;Abdallah, Maarof, & Zainal, 2016;Beránek, Nýdl, & Remeš, 2016;Gerlach, Pavlovic, & Gerlach, 2016;Lima & Pereira, 2016;Yang et al, 2016;Ramadhan & Amelia, 2016;Sun et al, 2017;Prisha, Neo, Ong, & Teo, 2017;Raghava-Raju, 2017;Shaji & Panchal, 2017;Wiralestari, 2017;Renjith, 2018;Weng et al, 2018;Zhao et al, 2018;Zheng et al, 2018); Amasiatu Amiruddin et al, 2019;Carta et al, 2019;Raghavan & Gayar, 2019;Shah et al, 2019;Soomro et al, 2019. Sementara penelitian lainnya lebih fokus pada penipuan sistem pembayaran dan penipuan terkait dengan pelanggan (Keraf & Hidup, 2010;Rofiq & Mula, 2010;Raj & Portia, 2011;Hu, Liu, & Sambamurthy, 2011;…”
Section: Pendahuluanunclassified
“…Tidak ada sistem deteksi penipuan yang sempurna, perlu ada pendekatan alternatif untuk mengantisipasi kegagalan yang terjadi dalam memerangi penipuan pada e-commerce. Misalnya dalam Zhao et al, (2018) penelitian berfokus pada penjual mereka yang dapat memaksimalkan laba platform, dan mengabaikan pengaruh pada perilaku penipuan penjual.…”
Section: Pemerintah Juga Berpartisipasi Dalam Menegakkan Hukum Yang Bunclassified
“…The previous name is: Learning to Advertise with Adaptive Exposure via Constrained Two-Level Reinforcement Learning. successful applications of DRL techniques to optimize the decisionmaking process in E-commerce from different aspects including online recommendation [11], impression allocation [10,41], advertising bidding strategies [19,37,40] and product ranking [16].…”
Section: Introductionmentioning
confidence: 99%
“…Table 6.1 summarizes the notations. 2 For simplicity, we assume that each product is sold only by one seller and each seller sells only one product. Gross Merchandise Volume (GMV) is a common metric for evaluating the scale of transactions, which is defined by the product of the total number of transactions and the average price of each transaction.…”
Section: Impression Allocation With Fraudulent Sellersmentioning
confidence: 99%
“…Unfortunately, the vulnerabilities of machine learning systems open a new door for the adversaries, who could potentially compromise a system by exploiting such vulnerabilities. The security of machine learning systems has been a critical concern for adversarial applications such as spam filtering, intrusion detection, malware detection and fraud detection in e-commerce [1,2].…”
Section: Introductionmentioning
confidence: 99%